gov.sandia.cognition.statistics.distribution

Class MultivariateGaussian.IncrementalEstimator

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner<DataType,SufficientStatisticsType>

gov.sandia.cognition.statistics.AbstractIncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic>

gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator

All Implemented Interfaces:

BatchAndIncrementalLearner<Vector,MultivariateGaussian.SufficientStatistic>, BatchLearner<java.util.Collection<? extends Vector>,MultivariateGaussian.SufficientStatistic>, IncrementalLearner<Vector,MultivariateGaussian.SufficientStatistic>, IncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

MultivariateGaussian

public static class MultivariateGaussian.IncrementalEstimator
extends AbstractIncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic>

The estimator that creates a MultivariateGaussian from a stream of values.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_COVARIANCE Default covariance, 1.0E-5.

Constructor Summary

Constructors

Constructor and Description
IncrementalEstimator() Default constructor
IncrementalEstimator(double defaultCovariance) Creates a new instance of IncrementalEstimator

Method Summary

Modifier and Type	Method and Description
MultivariateGaussian.SufficientStatistic	createInitialLearnedObject() Creates a new initial learned object, before any data is given.
double	getDefaultCovariance() Getter for defaultCovariance
void	setDefaultCovariance(double defaultCovariance) Setter for defaultCovariance

Methods inherited from class gov.sandia.cognition.statistics.AbstractIncrementalEstimator

clone, update

Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner

learn, learn, update

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchAndIncrementalLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner

learn

Methods inherited from interface gov.sandia.cognition.learning.algorithm.IncrementalLearner

update

Field Detail

DEFAULT_COVARIANCE

public static final double DEFAULT_COVARIANCE

Default covariance, 1.0E-5.

See Also:

Constant Field Values

Constructor Detail

IncrementalEstimator

public IncrementalEstimator()

Default constructor

IncrementalEstimator

public IncrementalEstimator(double defaultCovariance)

Creates a new instance of IncrementalEstimator

Parameters:

defaultCovariance - Default covariance of the distribution

Method Detail

getDefaultCovariance

public double getDefaultCovariance()

Getter for defaultCovariance

Returns:

Default covariance of the distribution

setDefaultCovariance

public void setDefaultCovariance(double defaultCovariance)

Setter for defaultCovariance

Parameters:

defaultCovariance - Default covariance of the distribution

createInitialLearnedObject

public MultivariateGaussian.SufficientStatistic createInitialLearnedObject()

Description copied from interface: IncrementalLearner

Creates a new initial learned object, before any data is given.

Returns:

The initial learned object.